Abstract It has been suggested that maximum latewood density (MXD) should be used instead of tree-ring width (TRW) data to reconstruct post-volcanic cooling effects. A thorough assessment of high frequency signals and potentially differing memory effects in long MXD and TRW chronologies, in response to large volcanic eruptions, is still missing, however. We here present a compilation of MXD and TRW chronologies from 11 sites in the Northern Hemisphere, covering the past 750+ years, and containing significant June–August temperature signals. Basic assessment of the data using Superposed Epoch Analysis reveals a temporally extended response in TRW, by 2–3 years, to large volcanic eruptions, though post-volcanic cooling patterns vary considerably within the Northern Hemisphere network. Comparison with instrumental temperature data demonstrates the TRW chronologies underestimate cold conditions associated with large volcanic eruptions, a bias that is mitigated in the MXD data. While species composition (pine, spruce, larch) has no detectable influence on the cooling patterns, trees from high latitude sites (>60°N) indicate a stronger and delayed (1–2 years) response to large eruptions, compared to the lower latitude sites (<60°N). These basic findings caution against using TRW data for quantitatively estimating post-volcanic cooling and for comparison against the simulated climate effects of volcanic eruptions in models.

This is the first of a two-part description of a new software tool CRUST (Climatic Research Unit Standardisation of Tree-ring data). This program has been designed primarily to allow the convenient, routine application of "Signal-Free Regional Chronology Standardisation" (SF RCS) to different types of tree-ring data. The program also enables the use of other popular standardisation methods. A series of experiments is described in which the ability of simple RCS and SF RCS to recover known tree-growth forcing signals is tested. In the comparatively rare situation where many sub-fossil data are distributed over a wide time range and there is no slope in the overall common-growth forcing signal, simple RCS is satisfactory. Simple RCS produces distortion in all other examples explored here. SF RCS is superior to simple RCS and in all cases examined. SF RCS works well except when the span of starting dates of sample trees is too narrow, a situation for which a test is available. Based on the results of the tests explored here, we conclude that Signal-Free RCS should be used as the standard method of RCS processing.

A number of processing options associated with the use of a "regional curve" to standardise tree-ring measurements and generate a chronology representing changing tree growth over time are discussed. It is shown that failing to use pith offset estimates can generate a small but systematic chronology error. Where chronologies contain long-timescale signal variance, tree indices created by division of the raw measurements by RCS curve values produce chronologies with a skewed distribution. A simple empirical method of converting tree-indices to have a normal distribution is proposed. The Expressed Population Signal, which is widely used to estimate the statistical confidence of chronologies created using curve-fitting methods of standardisation, is not suitable for use with RCS generated chronologies. An alternative implementation, which takes account of the uncertainty associated with long-timescale as well as short-timescale chronology variance, is proposed. The need to assess the homogeneity of differently-sourced sets of measurement data and their suitability for amalgamation into a single data set for RCS standardisation is discussed. The possible use of multiple growth-rate based RCS curves is considered where a potential gain in chronology confidence must be balanced against the potential loss of long-timescale variance. An approach to the use of the âsignal-freeâ method for generating artificial measurement series with the ânoiseâ characteristics of real data series but with a known chronology signal applied for testing standardisation performance is also described.

In this study, wood anatomy, tree-ring width and wood density of Pinus sylvestris at the northern timberline in Fennoscandia were used to identify relationships among the parameters and to screen them for their climatic signals. Furthermore we investigated the influence of the juvenile wood section for all parameters developed. The measurements of wood anatomy were conducted with confocal laser scanning microscopy (CLSM) while the density profiles were produced using an Itrax MultiScanner. We developed chronologies of ring width, wood density and anatomy for a period between 1940 and 2010. Correlations between wood density and wood anatomy were strong in the latewood part. For some wood anatomy and density chronologies youth trends were found in the juvenile part. Wood density decreased from the pith up to the 9th ring and stabilized afterwards, while cell lumen diameter and lumen area increased simultaneously up to the 15th ring. All chronologies contained strong summer temperature signals. The wood anatomical variables provided additional information about seasonal precipitation which could not be found in wood density and tree-ring widths. Our study confirmed previous results stating that the parameter maximum density contains the strongest climate signal, that is, summer temperatures at the northern timberline. Nevertheless, the intra-annual data on tracheid dimensions showed good potential to supply seasonal climatic information and improve our understanding of climatic effects on tree growth and wood formation.

Abstract Steinschneider et al. (2017) investigate model choices made in the hierarchical climate reconstruction approach of Schofield et al. (2016). We identify two flaws in their approach. The first is the use of an unusual approximation to Bayesian inference that unnecessarily discards important information. The second is that they mischaracterize the robustness of their reconstructions due to overlooking important features of the out-of-sample predictions. We demonstrate how full Bayesian inference can be conducted with no additional effort, providing R/JAGS code. We also show how graphical visualization of the out-of-sample predictions can lead to better understanding and comparison of the models fitted.

Abstract Tree-ring based paleoclimate reconstructions entail several sequential estimation or processing steps. Consequently, it can be difficult to isolate climatic from non-climatic variability in the raw ring width measurements, estimate the uncertainty associated with a reconstruction, and directly infer how specific techniques used to sequentially fit growth curves or to reconstruct climate influence the final estimates. This paper explores the use of hierarchical regression models to address these problems. The proposed models simultaneously model the entire reconstruction process in a way that is consistent with the existing step-by-step estimation framework, but allow for uncertainty estimation and propagation across steps, which can help determine how best to improve a candidate model. The utility of hierarchical models is tested for an example, the reconstruction of summertime temperatures in northern Sweden in a cross-validated framework relative to 1) a sequential process of growth curve fitting followed by chronology development, 3) an iterative, âsignal-freeâ approach, and 2) a signal-free regional curve standardization (RCS-SF). Further, an exploration of different structures within the unifying hierarchical framework is provided to illustrate how one could easily test a variety of choices of model design. We focus on a subset of choices relevant to recent dendroclimatic studies using hierarchical methods and related to 1) data transformation, 2) the benefits of biological detrending and climate reconstruction in a single step 3) partial pooling of the age model across trees, 4) the homogeneity of variance across tree-ring residuals, 5) the structural form of the age model, and 6) the inclusion of autoregressive processes for the tree-ring residuals. The work described here represents part of a series of ongoing explorations of potential advances over current dendroclimatic reconstruction approaches and commonly implemented ways in which they have and are specifically implemented. The results show that hierarchical modeling appears to offer improved climate reconstructions over the standardization techniques explored in this exercise, substantially so for the non-RCS sequential and iterative methods.